Prevalence of overweight and obesity in Canadian children, 2004 to 2013: Impact of socioeconomic determinants
Bibliographic record
Abstract
BACKGROUND: We recently reported an encouraging decline in the prevalence of overweight (OW) or obesity (OB) in Canadian children from 31% to 27% with stabilization in OB rates at ~13% using national survey data between 2004 and 2013. Although rates were lower for toddlers, girls and those of European (White) race-ethnicity, secular trends persisted after adjustment. In this follow-up study, we explored the ability of socioeconomic status to explain or modify these relationships using the same data set. METHODS: We analyzed a decade of anthropometric data from 14,014 children aged 3 to 19 years. We explored the influence of income adequacy, education, immigration status, family type (e.g., single-parent) and geographic region by multivariable logistic regression. Data sets included Canadian Community Health Survey cycle 2.2 and Canadian Health Measures Surveys cycles 2 and 3. RESULTS: Children from higher-income families fared better than their lower-income counterparts in each survey era and demonstrated a significant decline in OW/OB from 29.1% (95% confidence interval [CI]: 27.3 to 30.8) in 2004 to 2005 to 22.2% (95% CI: 19.8 to 24.6) in 2012 to 2013, P<0.001. Regression models confirmed the effects of time, age, sex, race, income, education, immigration and region. Although single-parent families did less well in univariate analyses, this effect vanished after adjustment for other socioeconomic status variables, such as income and education. Regional variations persisted, with lower rates of OB and OW/OB in British Columbia and higher rates in Atlantic Canada. CONCLUSIONS: These results confirm that progress is possible against this important public health challenge, underline the need to better understand sociodemographic risk factors and identify groups at higher risk for possible interventions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".